The Omnishopper Dilemma
How multi-location businesses can connect online advertising to offline sales.
By Amanda Martin
The omnishopper is a consumer who researches products online but goes to a physical store to purchase them. Seventy-six percent of omnishoppers end up doing most of their shopping research online, which means there is an incredible opportunity to influence the consumer’s eventual purchase through online advertising, but also an incredible gap in a marketer’s ability to measure that influence in terms of actual sales lift.
For businesses with multiple brick-and-mortar locations, the ability to address the problem and measure across that gap is compounded across stores. Not only does the national advertising strategy need to drive sales, but also each individual location needs a way to prove sales lift as well. Without the ability to prove digital advertising’s impact on sales, marketers struggle to justify their efforts to either their corporate or local dealers.
Fortunately, today, we have the tools to solve the omnishopper dilemma. Advertising technology allows us to tie online ads to offline sales at both the national and retailer level, giving marketers great insights into the most effective parts of their marketing plans and paving the way to ROI success.
Wrangling Offline Data
Most modern marketers and businesses know how to run ads online – that is not the hard part in solving the online-to-offline connection. The hard part is developing the strategy for how to collect, format and match back the offline data. There are two primary paths to get there: you either take the first-party path or the third-party path.
First-party – First-party data is offline and online purchase data you collect from your customers and own. A great example of first-party data is the customer information you collect as part of a shopper loyalty program. Within your own data, you can drill down into your customers’ profiles to better understand their interests and then segment them into specific audiences for online retargeting or look-alike modeling.
Over time, you’ll be able to measure the sales lift in relation to the advertising you ran against these various audience groups. The most common setback to this approach? All of your first-party data must be extremely clean – not an easy feat, especially with individuals hesitant to share their personally identifiable information (PII), which needs to be collected at the point of purchase, leading to the biggest part of the issue.
Third-party – If you don’t have a strong first-party data option or a company is unwilling to share their first-party data with outside sources (which is typically the case), there are likely many good third-party data options available to you. A good example of third-party data is the transaction data collected by a credit card company. This is not data you own, but it is data directly connected to offline sales that you can tie back to your digital advertising.
First-party data attribution is preferred but often not possible, and third-party data makes measurement more assessable. Third-party data companies and adtech companies have already done a lot of the heavy lifting on the backend to connect the information. Continuing with the example of credit card transaction data, the credit card company has already done the work to anonymize, format and connect user IDs to advertising IDs, making the actual matching work relatively seamless for the marketer.
In considering the first- versus third-party data path, you also need to understand the nuances of your industry vertical and the general accessibility of the various data options.
Automotive – Often, auto dealerships won’t share their purchase or CRM data with marketers and advertisers due to the competitive nature of the car-buying world. Rather, the industry has well-established and respected third-party data from companies like Polk/IHS Markit that dealers can use to better understand their sales and customers. A company like Polk, through its relationships with Oracle and other tech companies, can connect the dots between households who viewed a digital ad and also purchased a car. An analyst can set up a control versus exposed study using that information and derive a true auto purchase sales lift associated with digital advertising.
Restaurant – Due to the nature of the restaurant industry and the characteristics of a standard transaction, third-party credit card transaction data is an excellent source of offline data for marketers since so many customers pay using a credit card, at relatively frequent intervals. A restaurant marketer can work with a credit card company like MasterCard to isolate its own restaurant’s transactions and match those back to online ads. There are endless measurement possibilities, from understanding average transaction size to overall sales lift due to advertising influence. Connecting transaction data in this way provides the opportunity for one-to-one advertising, leading to a monetary amount.
Fitness – It might be tempting to think that credit card transaction data would also work well for fitness locations, but the hurdle here is that there is usually less purchase activity happening at the location itself. Customers might sign up for a package in one transaction or they might sign up for classes online, making it difficult to reach the feasibility threshold that credit card transaction companies require. So, a good online-to-offline strategy for fitness locations is to focus on tying back foot traffic to advertising exposure. Foot traffic is a great indicator for understanding which ads are actually driving visitors, and to which stores in which markets, providing great clarity when reworking a digital ad budget.
With all the product advancements in data and advertising, it might seem relatively easy to connect online advertising to offline sales for your business. Before diving in, however, you should understand and anticipate the roadblocks that might hinder your success with this technique.
One of the biggest hurdles for any business trying to connect online and offline data is having enough data. Both the digital campaign data and the offline data need to be sizeable enough to reach statistical relevance in order to confidently report back on results. What makes this more complex to gauge is that there is no set definition of what “enough” data looks like.
For example, a campaign with 50 million impressions over a month might be enough for a QSR with a high number of in-store purchases, but it might not be nearly enough for a furniture store with significantly lower transaction volume and a longer purchase cycle. To overcome some of these hurdles, location marketers can adjust the granularity of the analysis by grouping together stores, zones or regions and align the marketing strategy accordingly.
Additionally, it’s important for local businesses to create an ad strategy outside of their national branding. A lot of businesses rely on the branding of a corporate entity, but it is equally as important for the local store to ensure consumers know where they are located. Take a consumer that needs to get their oil changed. They probably have brand awareness of local options available but may be more driven to a location based on the offering price. Advertising your location-based special is what will get them in your garage vs. the competitions. While people are aware of the corporate brand, it’s important for the local franchise to put themselves on the map.
With the roadblocks in mind, there are upsides to multilocation franchises. It’s easier to simplify and understand purchase data, as marketers of multi-franchises don’t face the hurdles of big-box stores, where it’s harder to figure out who bought the specific product. In stores like Target and Walmart, brands know consumers purchased their products, but have no further insights into who made the purchase. Not only does this make it harder for retargeting efforts, it’s also challenging to understand lift and impact of online ads on offline purchases.
By utilizing franchise-level advertising, marketers can quickly see sales lift due to the branding effort per location. Offline sales measurement is valuable, but the methodology behind these campaigns are crucial.
Amanda Martin is director of enterprise partnerships for Goodway Group.